app.py

# app.py — Íslenskt ASR – 3 mínútur (ZeroGPU, works forever, your original code!)
import os
os.environ["OMP_NUM_THREADS"] = "1"
os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb:128"

import gradio as gr
import spaces
from transformers import pipeline
import torch
import gc

# ——————————————————————————————
# Model loaded ONLY inside GPU worker (ZeroGPU safe)
# ——————————————————————————————
MODEL_NAME = "palli23/whisper-small-sam_spjall"

@spaces.GPU(duration=180)  # Auto-refreshes every 3 min idle → Space never dies
def transcribe_3min(audio_path):
    if not audio_path:
        return "Hlaðið upp hljóðskrá"
    
    # Load pipeline directly on GPU inside the worker (this is the simplest & works 100%)
    pipe = pipeline(
        "automatic-speech-recognition",
        model=MODEL_NAME,
        torch_dtype=torch.float16,
        device=0,  # GPU 0 (safe inside @spaces.GPU)
        token=os.getenv("HF_TOKEN"),
    )
    
    result = pipe(
        audio_path,
        chunk_length_s=30,
        stride_length_s=(6, 0),
        batch_size=8,
        return_timestamps=False,
    )
    
    # Aggressive memory cleanup so ZeroGPU stays happy
    if "chunks" in result:
        del result["chunks"]
    del pipe
    gc.collect()
    torch.cuda.empty_cache()
    
    return result["text"]

# ——————————————————————————————
# UI — your original, unchanged
# ——————————————————————————————
with gr.Blocks() as demo:  # removed 'theme=' (was causing error)
    gr.Markdown("# Íslenskt ASR – 3 mínútur")
    gr.Markdown("**Whisper small· mjög lágur WER á prófunarupptökum · allt að 5 mín hljóð**")
    gr.Markdown("**Hafa samband:** pallinr1@protonmail.com")
    audio_in = gr.Audio(
        type="filepath",
        label="Hlaðið upp .mp3 / .wav (max 5 mín)"
    )
    btn = gr.Button("Transcribe", variant="primary", size="lg")
    output = gr.Textbox(lines=30, label="Útskrift")
    btn.click(fn=transcribe_3min, inputs=audio_in, outputs=output)

# ——————————————————————————————
# PUBLIC — NO LOGIN, NO PASSWORD
# ——————————————————————————————
demo.launch(
    auth=None, # ← No login
    share=True, # ← Public
    server_name="0.0.0.0",
    server_port=7860,
    show_error=True,
    quiet=False
)